Rezaei Tavirani Mostafa, Rezaei Tavirani Majid, Zamanian Azodi Mona
Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Gastroenterol Hepatol Bed Bench. 2019 Spring;12(2):131-137.
Identification of prominent genes which are involved in onset and progress of steatosis stage of Nonalcoholic fatty liver disease (NAFLD) is the aim of this study.
NAFLD is characterized by accumulation of lipids in hepatocytes. The patients with steatosis (the first stage of NAFLD) will come across nonalcoholic steatohepatitis (NASH) and finally hepatic cirrhosis. There is correlation between cirrhosis and hepatic cancer. However, ultrasonography is used to diagnose NAFLD, biopsy is the precise diagnostic method.
Gene expression profiles of 14 steatosis patients and 14 controls are retrieved from gene expression omnibus (GEO) and after statistical validation top 250 differentially expressed genes (DEGs) were determined. The characterized DEGs were included in network analysis and the central DEGs were identified. Gene ontology (GO) performed by ClueGO analysis of DEGs to determine critical biological terms. Role of prominent DEGs in steatosis is discussed in details.
Numbers of 31 significant DEGs including 20 up-regulated and 11 down-regulated ones were determined. Nine biological groups including 27 terms were recognized. Negative regulation of low-density lipoprotein particle receptor catabolic process, TRAM-dependent toll-like receptor signaling pathway, and regulation of hindgut contraction which were related to ANXA2, PRKCE, and OXT respectively were determined as critical biological term groups and DEGS.
Deregulation of ANXA2, PRKCE, and OXT is a critical event in steatosis. It seems these three genes are suitable biomarker to diagnosis of steatosis.
本研究旨在鉴定参与非酒精性脂肪性肝病(NAFLD)脂肪变性阶段发生和进展的重要基因。
NAFLD的特征是肝细胞中脂质积累。脂肪变性患者(NAFLD的第一阶段)会发展为非酒精性脂肪性肝炎(NASH),最终发展为肝硬化。肝硬化与肝癌之间存在关联。然而,超声检查用于诊断NAFLD,活检是精确的诊断方法。
从基因表达综合数据库(GEO)中检索14例脂肪变性患者和14例对照的基因表达谱,经过统计验证后确定前250个差异表达基因(DEG)。将特征性DEG纳入网络分析并鉴定核心DEG。通过对DEG进行ClueGO分析来进行基因本体(GO)分析,以确定关键生物学术语。详细讨论了重要DEG在脂肪变性中的作用。
确定了31个显著的DEG,包括20个上调和11个下调的DEG。识别出9个生物组,包括27个术语。分别与ANXA2、PRKCE和OXT相关的低密度脂蛋白颗粒受体分解代谢过程的负调控、TRAM依赖的Toll样受体信号通路以及后肠收缩的调控被确定为关键生物学术语组和DEG。
ANXA2、PRKCE和OXT的失调是脂肪变性中的关键事件。这三个基因似乎是诊断脂肪变性的合适生物标志物。